我国航空货运市场发展趋势探析

本文深入分析了当前我国航空货运业面临的国际和国内政治经济形势,结合全球经济与航空货运业发展趋势,深入研究了我国航空货运业的发展方向。     

我国航空货运市场发展趋势屎析

摘要：本文深入分析了当前我国航空货运业面临的国际和国内政治经济形势，结合全球经济与航空货运业发展趋势，深入研究了我国航空货运业的发展方向。     

2018年航空货运市场回顾与2019年展望

2018年全球航空货运市场持续疲软,需求增长率连续走低,中美贸易战前途未卜,在这种背景下,我国航空货运市场曲折前行。本文主要回顾了2018年全球航空货运市场以及中国航空货运市场现状,再以航空货运市场的货源结构、技术变革、发展模式为切入点,重点总结了2019年适合我国航空货运市场涉足的领域,为我国航空货运业的发展提供了可借鉴的新思路。     

美国航空货运安保供应链研究

航空货运安保供应链作为航空货运业的重要组成部分，对于加快形成内外联通、安全高效的航空物流网络具有重要意义。本研究通过梳理美国航空货运安保管理机构及法规体系，分析了美国航空货运安保供应链的建设背景与基本策略，重点论述了在国际民航组织（ICAO）安保供应链六大支柱的基础上，美国航空货运安保供应链的框架和基本要求，并得到了对我国航空货运安保供应链建设的启示：一是完备的政策法规体系为航空货运业发展指引方向；二是良好的社会信用制度为航空货运安保供应链建设奠定基础；三是标准化体系为航空货运安保供应链发展提供保证。     

广东省道路货运业与经济发展相关性分析

本文主要研究了广东省道路货运业与国民经济发展的联系,进行相关性分析。在总结、梳理广东省道路货运业与国民经济发展现状的基础上,选取能够代表道路货运业发展的相关经济指标(道路货运量、道路货运周转量),对数据进行整理分析,并计算其与国民经济相关指标(GDP、第二产业增加值、第三产业增加值)的相关系数,结果显示道路货运业与第三产业增加值的相关程度更高,并对相关的指标进行一元线性回归分析,得出广东省道路货运业基础设施完善,运输供给充足,同时广东省道路货运服务水平与宏观的发展具有较高的相关性,对经济发展具有促进作用。     

从WTO到建设道路货运市场主体的思考

一、建设道路货运市场主体的必要性和紧迫性 今年5月份,随着中国与欧盟就中国加入WTO达成双边协议和美国国会众议院通过给予中国永久性正常贸易关系(PNTR),中国加入WTO指日可待。要知道,在乌拉圭回合谈判期间及后来的加入WTO的谈判过程中,几乎未涉及道路货运的内容;直到1992年2月份,美国在与我国进行加入WTO谈判中,才在分销服务项下提出开放道路货运市场的要求。这说明快速发展、日益强盛的中国经济所带动的道路货运业的巨大发展潜力对发达国家具有很强的吸引力;同时也说明发达国家实力强劲的跨国货运企业将     

2016年航空货运市场回顾与2017年展望

2016年世界航空货运渐入佳境,局部地区出现大幅增长,而我国航空货运市场喜忧参半。本文主要回顾了2016年世界航空货运市场以及中国航空货运市场现状,再根据业内普遍看好和唱衰的几个关键点入手,重点展望了我国2017年航空货运市场,为我国航空企业发展提出了可行的方向。     

新疆公路货运业发展现状分析及建议

一、新疆公路货运业的现状分析新疆维吾尔自治区位于我国的西北边疆、欧亚大陆中部。2003年新疆货物运输总货运量为37484.8万吨,其中公路货运完成货运量30881万吨,占全区货物运输总货运量比重的82.38%。新疆公路货运周转量为325亿吨公里,在铁路、公路、民航、管道四种运输方式中占38.83%,可见公路货运市场是新疆综合货运市场中最大的子市场。公路货运在带动新疆经济发展过程中发挥着举足轻重的作用,但是在新疆公路货运发展的过程中存在着一些问题,这些问题阻碍了其健康、快速发展。下面将从宏观管理环境、服务体系建设两方面进行现状分析。(…     

绿色音符跃动北京——记首届中国绿色货运专题研讨会在京举行

下一步,货运业节能减排的路径有哪些?绿色货运能否加速中国道路货运业的转型升级?6月中旬,由亚洲城市清洁行动中心主办,交通运输部道路运输司、美国国家环境保护局、世界银行、美国CSS组织支持的首届中国绿色货运专题研讨会给出了自己的解答。此次研讨会的目的在于推动绿色货运项目在中国的推广和应用。     

“十三五”时期我国发展航空货运枢纽的战略选择

"十三五"时期是我国规划发展以航空货运为主体的枢纽机场的重要机遇期。本文分别从机场和航空货运企业角度,论证了航空货运枢纽的形成机理,总结了建设航空货运枢纽的国际经验,提出了航空货运枢纽的决策支持分析方法,提出在我国中部地区建设一个服务全国的航空货运枢纽机场、促进航空物流业态创新和临空经济结构转型的政策建议。     

A linear programming-based method for the network revenue management problem of air cargo

One critical operational issue of air cargo operation faced by airlines is the control over the sales of their limited cargo space. Since American Airlines’ successful implementation in the post-deregulation era, revenue management (RM) has become a common practice for the airline industry. However, unlike the air passenger operation supported by well-developed RM systems with advanced decision models, the decision process in selling air cargo space to freight forwarders is usually based on experience, without much support from optimization techniques. This study first formulates a multi-dimensional dynamic programming (DP) model to present a network RM problem for air cargo. In order to overcome the computational challenge, this study develops two linear programming (LP) based models to provide the decision support operationally suitable for airlines. In addition, this study further introduces a dynamic adjustment factor to alleviate the inaccuracy problem of the static LP models in estimating resource opportunity cost. Finally, a numerical experiment is performed to validate the applicability of the developed model and solution algorithm to the real-world problems.     

Cargo Container Loading Plan Model and Solution Method for International Air Express Carriers

Abstract

In this article, a cargo container loading plan model is developed based on the operations of FedEx, the international air express carrier. The objective is to minimize total container handling cost, subject to related operating constraints. The model is expected to be a useful planning tool whereby international air express carriers such as FedEx can decide on container loading plans that will lead to lower operating costs, thus enhancing profits and market competitiveness. The model is formulated as a non-linear mixed integer program that is characterized as NP-hard. A solution method is then developed, with the use of the mathematical programming solver, CPLEX, to solve the problem efficiently. To evaluate the model and the solution method, we perform a case study using data from FedEx. The preliminary results indicate that the model and the solution method are both efficient and effective.     

Determinants of air cargo traffic in California

Studies on the economic impacts of air cargo traffic have been gaining traction in recent years. The slowed growth of air cargo traffic at California’s airports, however, has raised pressing questions about the determinants of air cargo traffic. Specifically, it would be useful to know how California’s air cargo traffic is affected by urban economic characteristics. Accordingly, this study estimates the socioeconomic determinants of air cargo traffic across cities in California. We construct a 7-year panel (2003–2009) using quarterly employment, wage, population, and traffic data for metro areas in the state. Our results reveal that the concentrations of both service and manufacturing employment impact the volume of outbound air cargo. Total air cargo traffic is found to grow faster than population, while the corresponding domestic traffic grows less than proportionally to city size. Wages play a significant role in determining both total and domestic air cargo movement. We provide point estimates for traffic diversion between cities, showing that 80% of air cargo traffic is diverted away from a small city located within 100 miles of a large one. Using socioeconomic and demographic forecasts prepared for California’s Department of Transportation, we also forecast metro-level total and domestic air cargo tonnage for the years 2010–2040. Our forecasts for this period indicate that California’s total (domestic) air cargo traffic will increase at an average rate of 5.9% (4.4%) per year.     

Air cargo operations: Literature review and comparison with practices

This study reviews the literature on air cargo operations and compares theoretical studies with the practical problems of airlines, freight forwarders, and terminal service providers. In particular, we review studies in which mathematical models were used to identify the essential characteristics of air cargo operations, such as the intrinsic differences from passenger operations, and to explore the service processes in air cargo operations. The typical models used in previous studies are summarized. We then highlight the insightful findings from an industrial interview and present the gaps between previous research and practical realities. We finally discuss the new research opportunities of air cargo operations according to the gaps.     

Empirical estimation of price and income elasticities of air cargo demand: The case of Hong Kong

This paper estimates the price and income elasticities of air cargo demand and examines how they may change after the 2008 financial crisis. Using a set of time series data, we simultaneously estimate the aggregated demand and supply functions of air cargo at Hong Kong International Airport (HKIA). We find that during the entire sampling period of 2001–2013, the price elasticity for air cargo transport demand at HKIA ranges from −0.74 to −0.29, suggesting that air cargo demand in Hong Kong reacts negatively to price (as expected) but does not appear to be very sensitive to price. The income elasticity ranges from 0.29 to 1.47 and appears sensitive to seasonality adjustment approaches. However, in terms of the speed of changes, air cargo demand changes much faster than overall economy, indicating the presence of a pro-cyclical pattern of air cargo traffic with respect to the overall economy. Our analysis shows that air cargo demand becomes more sensitive to changes in both price and income after 2008.     

Assessment of carbon emission costs for air cargo transportation

This study presents a set of models that calculate carbon emissions in individual phases of flight during air cargo transportation, investigates resultant carbon footprints by aircraft type and flight route, and estimates increases in transportation costs for airlines due to carbon taxes imposed by the EU ETS. The estimated results provide useful references for airlines in aircraft assignment on different routes and in aircraft selection for new purchases. Validation of the model is conducted by simulating the potential impact of the implementation of the EU ETS on costs of air cargo transportation for six routes and six types of aircraft. Results show that the impact may be subject to various factors including unit carbon emissions per aircraft, aviation emission allowances per airline, and carbon trading prices; and that increases in costs of air cargo transportation range from 0% to 5.27% per aircraft per route. Therefore, the implementation of the EU ETS may encourage airlines to cut down their operating costs by reducing their carbon emissions, thereby ameliorating greenhouse gas pollution caused by air cargo transportation.     

Improving the forecasting accuracy of air passenger and air cargo demand: the application of back-propagation neural networks

This study employs back-propagation neural networks (BPN) to improve the forecasting accuracy of air passenger and air cargo demand from Japan to Taiwan. The factors which influence air passenger and air cargo demand are identified, evaluated and analysed in detail. The results reveal that some factors influence both passenger and cargo demand, and the others only one of them. The forecasting accuracy of air passenger and air cargo demand has been improved efficiently by the proposed procedure to evaluate input variables. The established model improves dramatically the forecasting accuracy of air passenger demand with an extremely low mean absolute percentage error (MAPE) of 0.34% and 7.74% for air cargo demand.     

A Lagrangian relaxation based heuristic for the consolidation problem of airfreight forwarders

International air cargo is an operation-intensive industry, involving complex procedures and many players. As an important player, airfreight forwarders need to consolidate the collected goods skillfully in order to satisfy the requirements of the shippers and, at the same time minimize the expense charged by the airlines. However, the air cargo rate structure is very complicated, making the consolidation a difficult mixed-integer programming problem for the airfreight forwarder. In this paper, the consolidation problem is first transformed into a well-known set covering problem by treating a feasible consolidated shipment as a set. Lagrangian Relaxation is used as the backbone to develop a recursive heuristic algorithm. Based on the numerical experiment, the heuristic algorithm generates solutions very close to optimality. In particular, a sensitivity analysis is performed with respect to the degree of concavity. The results suggest that the solution algorithm can be used as a core module of the decision support system for air cargo consolidation.     

A time series analysis of the dynamic competition between major cargo airports

This paper models the dynamic competition between major cargo airports from the time series perspectives of long-term equilibriums and short-run dynamics. We first apply a unit root test to examine the stationarity of cargo throughput data. Airports are then analysed pairwise by region to test their equilibrium relationships through cointegration analysis. Meanwhile, we also utilise the error correction model to investigate the short-run impacts of cargo traffic between the airports. According to our findings, there are four positive long-term equilibriums, one positive short-run dynamic and three negative short-run dynamics in Asia. In addition, the airports in North America are found to have four positive long-term equilibriums, three negative long-run equilibriums, seven positive short-run impacts and three negative short-run impacts. As these dynamic relationships imply competition between cargo airports, our study can provide airport authorities with the reference to develop their long-term strategies and short-run operational plans.     

Optimal shipment decisions for an airfreight forwarder: Formulation and solution methods

We study the freight forwarder’s shipment planning problem in an airfreight forwarding network where a set of cargo shipments have to be transported to given destinations. We provide mixed integer programming formulations that use piecewise-linear cargo rates and account for volume and weight constraints, flight departure/arrival times, as well as shipment-ready times.After exploring the solution of such models using CPLEX, we devise two solution methodologies to handle large problem sizes. The first is based on Lagrangian relaxation, where the problems decompose into a set of knapsack problems and a set of network flow problems. The second is a local branching heuristic that combines branching ideas and local search. The two approaches show promising results in providing good quality heuristic solutions within reasonable computational times, for difficult and large shipment consolidation problems.